Field
The invention relates to an autonomous vehicle with a computing unit to perform a mapping function and a localization function of the vehicle within the map, in particular an autonomous gardening tool such as an autonomous lawn mower or scarifier and a system with such autonomous vehicle and a boundary wire indicating a border of an area in which autonomous driving of the autonomous vehicle shall be performed.
Description of the Related Art
Over the past few years, it became more and more popular to substitute tools like vacuum cleaners, lawn mowers or scarifier by self-propelled devices that are capable of driving on their own. Thus, no operator is needed that pushes and controls direction of such devices. Of course, the functionality of these devices has been improved over the product cycles up to now. Nevertheless, there are some disadvantages that might be annoying for some users. Maybe the biggest problem is that the driving direction of these devices is determined by chance without knowing anything about the layout of the environment and so the vacuum cleaner or the lawn mower drives around randomly which results inefficiently working on the dedicated area. To improve the devices in that regard, so-called SLAM techniques that are known from the robotic's domain have been introduced also for the autonomous vehicles. SLAM (Simultaneous Localization And Mapping) is the ability to generate a map without human intervention combined with the ability to localize within this map. The self-localization of the autonomous vehicle can be performed even if the process of generating the map is still in progress.
For SLAM typically data from odometry, laser scanners and cameras is used. The problem is that the better the SLAM result shall be, the more expensive the sensors that provide good results are. For example, laser scanners yield good results, but are much more expensive than other sensors. On the other side, odometry and camera data, which would be much cheaper to implement than the laser scanners, can be used for indoor environments without any problem, because they lead to robust SLAM results. But unfortunately, outdoor environments are much more difficult. Thus, in order to provide a vehicle with SLAM-function feasible for outdoor environments also, the SLAM results have to be improved.
Previous proposals for outdoor applications describe different solutions for autonomous vehicles that do not use the SLAM technique. Since also for other, for example camera-based, approaches (obstacle detection) there is a problem that in outdoor environment the lighting conditions may change significantly, U.S. Pat. No. 8,958,939 proposes to adjust the speed of the autonomous vehicle to compensate for varying exposure times for the camera.
Further, US 2010/0324731 describes an interaction between a user and a lawn mower via Smartphone. The mower uses a map that is generated by means of parameter teaching, but of course this means a great effort necessary for the user. Such an effort could be avoided if a robust SLAM technique would be available even for outdoor applications.
But all these approaches cannot compete with SLAM and the opportunities resulting therefrom. Thus, it is an object of the present invention to provide an autonomous vehicle with an improved SLAM capability
The problem is solved with the autonomous vehicle and the system including such autonomous vehicle according to the independent claims.
To achieve the object, an autonomous vehicle is suggested that comprises a driving means for self-propelling the autonomous vehicle. The vehicle further comprises at least one environment sensing means for sensing an environment of the vehicle. Such sensing means provides a signal including information perceived to a computing unit that is configured to perform a mapping function and a localization function. The mapping function is performed on the basis of the signal or the signals in case of a plurality of sensors in order to generate or build up a map. With a localization function, localization information on the autonomous vehicle within the map is generated.